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| license: mit |
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| Details on the code used to produce and use this model are available at: |
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| https://github.com/schrum2/MarioDiffusion |
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| That repo has instructions to check out this model and apply it to the generation of Super Mario Bros. level scenes. |
| There is also an interactive GUI for constructing complete levels out of model-generated scenes. |
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| This model makes use of https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5 |
| as a text embedding model for use with diffusion to generate Mario levels. |
| It makes use of negative guidance during diffusion training, and encodes each |
| of several phrases within each caption as a distinct text embedding. |
| Our results indicate that it has relatively poor performance, so it is made available |
| only to allow full scrutiny of our results. |
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| To see a model using Alibaba-NLP/gte-large-en-v1.5 that performs better with |
| multiple text embeddings without using negative guidance, |
| see https://huggingface.co/schrum2/MarioDiffusion-GTE-multiple-regular0. |
| To see a model that uses |
| a simple token-based transformer model for text embedding |
| and makes use of negative guidance, see https://huggingface.co/schrum2/MarioDiffusion-MLM-negative0. |
